Monitor
Continuously monitor your AI applications for hallucinations, quality regressions, and performance drift in production.
Defend
Catch hallucinations in real time and automatically correct them before they reach your users.
The Challenge - Evaluating Model Performance
“Lack of evaluations has been a key challenge for deploying to production”AI systems can generate significantly varied outputs for identical inputs, complicating benchmarks and making consistent evaluation difficult. Current evaluation methods struggle to identify subtle inaccuracies, hallucinations, or early indicators of performance drift, exposing organizations to critical risks. Additionally, as models evolve, previously reliable methods quickly become obsolete. This requires the need for evaluation tools that keep pace with continuous changes in AI behavior to consistently provide trustworthy insights and guardrails against critical failures.
- OpenAI, DevDay Conference
”.. don’t consider prompts the crown jewels. Evals are the crown jewels”The best performing prompts are guided by continuous rounds of high quality evaluations.
- Jared Friedman, Y Combinator Lightcone Podcast
What Makes DeepRails Unique
Most AI safety tools stop at detection: they flag problems, block outputs, or log failures for you to handle later. DeepRails goes further. The Defend API corrects hallucinated responses automatically, so your users always get accurate answers.- Monitor API: Real-time detection and observability
- Defend API: Real-time detection + automatic correction
